The present invention relates to the field of the operation and maintenance of industrial turbomachinery. In particular, the invention relates to monitoring and tracking the operation of turbomachinery, predicting the operational life of the turbomachinery and its parts, and scheduling maintenance for the turbomachinery.
Gas turbines generally include a compressor and turbine arranged on a rotating shaft(s), and a combustion section between the compressor and turbine. The combustion section burns a mixture of compressed air and liquid and/or gaseous fuel to generate a high energy combustion gas stream that drives the rotating turbine. The turbine rotationally drives the compressor and provides output power. Industrial gas turbines are often used to provide output power to drive an electrical generator or motor. Other types of gas turbines may be used as aircraft engines, on-site and supplemental power generators, and for other applications.
Gas turbines have many parts and components that are exposed to corrosive combustion gases, extreme temperatures, centrifugal stresses and other adverse conditions. These conditions impose stresses and corrosive elements on the gas turbine that cause wear, strain, fatigue, corrosion and other harmful effects. Moreover, the major rotating components, e.g., shaft, turbine and compressor, sustain stresses and are critical to the operation of the gas turbine.
In addition, the compressor, combustion section and turbine form a gas-path for the air and combustion gases that flow through the gas turbine. These gas-path components withstand extremely high energy loads, temperatures and corrosive gases. The elevated temperatures, high stresses and aggressive environmental conditions create time-dependent and cyclic failure mechanisms that act on the gas turbine, and especially the gas path components of the gas turbine. These conditions can lead to failure of components of the gas turbine and, possibly, failure of the gas turbine itself.
The gas turbine components that generally require much attention to maintenance are those associated with the combustion process, e.g., combustion chambers (cans), combustion liners, end caps, crossfire tubes, turbine nozzles, turbine buckets, etc. These xe2x80x9chot-gas-pathxe2x80x9d components tend to be those that require regular replacement, and are the subject of regular preventive maintenance and replacement programs. In addition, other basic gas turbine components, such as control devices, fuel metering equipment, gas turbine auxiliaries, load packages, and other station auxiliaries require periodic servicing.
Preventive maintenance safeguards industrial gas turbines from failure and undue wear of components. Preventative maintenance requires a maintenance schedule to be established for each gas turbine. The schedule is created based on the operating history of the gas turbine. The technicians who operate the gas turbines maintain detailed and comprehensive logs of their operation, including the start-stop times, operating conditions, fuel, load and other conditions. Using these logs, the technicians and supervising engineers monitor the operation of the gas turbine and schedule preventive maintenance and parts replacements.
In recent years, control systems for gas turbines have been developed that collect data from sensors on the turbine. This data reflects the operating condition of the gas turbine, in a manner similar to the data manually logged by earlier technicians. Accordingly, some of the manual logging of operating conditions have been replaced by automatic data collecting control systems.
Manufacturers of gas turbines generally provide instructional manuals as to how to monitor the gas turbine and schedule maintenance and repairs. For example, the Power System Division of the General Electric Company provides a manual entitled xe2x80x9cHeavy-Duty Gas Turbine Operating and Maintenance Considerationsxe2x80x9d (GER-3620G) that explains how to create maintenance schedules for gas turbines and how to conduct preventive maintenance. By following the instructions described in the manual, a technician evaluates the logged operating history of a gas turbine and determines when and what preventive maintenance should be performed.
Prior techniques for scheduling maintenance for industrial gas turbines relied on algorithms that predicted the expected operating life of various components of the turbine. These algorithms for predicting component life are typically based on a defined xe2x80x9cdesign duty cyclexe2x80x9d, which is a standardized operational cycle for the gas turbine or one of its components. The design duty cycle is used to predict the deterioration of parts in a gas turbine during a standard cycle of starting, a power production (which may be constant or variable) period and shut-down. The design duty cycle simulates the actual deterioration of parts in a gas turbine operating under conditions for the turbine was designed. However, the design duty cycle does not truly reflect the actual operating conditions of a gas turbine, actual operating conditions are often substantially different than those for which the gas turbine was designed.
The actual maintenance requirements of a gas turbine depend on its actual operational history, which includes the actual operating conditions. The actual life of a gas turbine is a strong function of actual usage of that turbine. Off-design operating conditions and off-design modes (e.g., operating conditions substantially different than duty cycle conditions) affect metal temperatures and stresses, and result in more (or less) than predicted damage to the gas turbine. To reflect off-design conditions, prior techniques have used xe2x80x9cmaintenance factorsxe2x80x9d to supplement the duty cycle analysis. xe2x80x9cMaintenance factorsxe2x80x9d quantify the severity of off-design operation. Maintenance factors have been manually determined by gas turbine technicians and engineers.
Conventional methods of predicting part failure for gas turbines and scheduling maintenance have not been entirely accurate in predicting part failures or optimally scheduling maintenance. The traditional xe2x80x9cduty cyclexe2x80x9d used for predictive maintenance does not reflect real operational conditions, especially off-design operations. The actual life of a component of a gas turbine depends strongly on the actual usage of that gas turbine and the part within the turbine. For example, elevated temperatures and stresses within the turbine, and aggressive environmental conditions may cause excessive wear on components in the turbine beyond that predicted with the standard design duty cycle. Off-design operating conditions, which are often experienced by industrial gas turbines, are not reflected by the standard duty cycles. The actual part life of components in the gas turbine may be substantially less than that predicted by the design duty cycle. Alternatively, if more favorable conditions are experienced by an actual gas turbine (than are reflected in the design duty cycle), the actual part life may last substantially longer than that predicted by maintenance schedules based on the design duty cycle. In either event, the standard xe2x80x9cdesign duty cyclexe2x80x9d model for predicting preventive maintenance in industrial gas turbines does not reliably indicate the actual wear and tear experience by a gas turbine. Accordingly, there is a long-felt need for a technique to more accurately predict the life of a gas turbine and its components.
Prior techniques for predicting maintenance and part replacement relied on skilled technicians to acquire or interpret data regarding the operation of a gas turbine. Such techniques were subject to the varying interpretations of that data by technicians. The operational logs and/or data collected from gas turbines were manually evaluated by technicians. Technicians, for example, would evaluate start and stop times, and power settings to determine how many duty cycles had been experienced by the gas turbine, their frequency, period and other factors. In addition, if the log data of the gas turbine indicated that extraordinary conditions existed, such as excessive temperatures or stresses, the technicians would apply xe2x80x9cmaintenance factorsxe2x80x9d to quantify the severity of these off-design operational conditions.
A system has been developed to automatically capture and analyze operational data from industrial gas turbines. The data is analyzed by the system to determine expected component wear and deterioration in the gas turbine. Based on the analysis, reports are generated by the system that may be used to schedule maintenance for the gas turbine.
Algorithms have been developed to analyze the operational data from each gas turbine. These algorithms may calculate the operational exposure of a gas turbine in terms of xe2x80x9cfactored hourxe2x80x9d, xe2x80x9cfactored startsxe2x80x9d, and conventional standards previously used for evaluating maintenance periods in gas turbines. In addition, precise definitions have been developed for various gas turbine events and conditions, such as start and stop conditions. These definitions facilitate the automatic analysis by computers of data collected from the gas turbine. The definitions are applied by computers to identify the occurrence of specific events, e.g., starts, stops and load, and operating modes of a gas turbine based on operational data acquired from the gas turbine. These events and modes are evaluated by the computer using algorithms to generate information regarding the operational events and modes of the gas turbine that are useful in scheduling maintenance of the gas turbine.
The system may be used to provide inspection and repair scheduling services for operators of industrial gas turbines. For example, data collected remotely from operational gas turbines may be evaluated and used to generate automatic maintenance scheduling reports. These reports schedule outages, i.e., periods during which the gas turbine is to be shut down for maintenance. In addition, the reports may list parts to be ordered and on hand during the scheduled outages for replacement in the gas turbine.
These reports of a maintenance schedule and components to be replaced are provided by the system to maintenance technicians. The reports may be in the form of charts that show the times of various modes of gas turbine operation. Based on these charts, a technician can readily schedule appropriate maintenance for a gas turbine.
The technicians avoid having to undergo the laborious task of reviewing operational logs of the turbine and determine the operational times of the various modes of the gas turbine. In addition, the system generates information based on actual operational data from the individual gas turbines. Thus, reports generated by the system are optimized for scheduling maintenance.
The system has been designed such that its algorithms, definitions and data collection techniques can be readily modified as needed. For example, if it is determined that certain maintenance is being scheduled too infrequently, the algorithm for that particular type of maintenance may be adjusted so as to schedule maintenance more frequently.